Inputting text-based passwords on a device that receives input primarily via a touchscreen is often unwieldy and time-consuming. The quality of text-based passwords can be calculated, and based on the quality the user can be informed of whether the selected password would be difficult to crack. Many touchscreen devices, such as smartphones and tablets, use pin-based or pattern-based authentication schemes (e.g., for unlocking the device). These schemes typically have limited password spaces, which can cause the device and/or information protected by the schemes to be less secure. Gesture-based passwords have been proposed as a way to both provide greater security through a larger password space, as well as easier entry of the password by utilizing the touchscreen functionality directly rather than by opening a keyboard. For example, a gesture-based password scheme can allow a user to choose any image, and use that image as a background for a gesture-based password (e.g., including tap, line and circle gestures) that can represent the user's knowledge of the gesture-based password and its correspondence to the selected image. However, techniques for measuring password quality for such gesture-based passwords do not exist, and therefore a user may inadvertently choose an easily cracked gesture-based password believing it to be secure.
Accordingly, it is desirable to provide methods, systems, and media for measuring quality of gesture-based passwords.